Search

Background: Monoclonal antibodies (mAbs) undergo multiple post-translational modifications (PTMs) during production and storage, resulting for instance in charge and oxidized variants. PTMs need to be assessed as critical quality attributes to assure protein quality and safety. Capillary zone electrophoresis (CZE) enables efficient charge-based separation. The CZE method developed by He et al. (2011) is currently applied routinely in the pharmaceutical industry for profiling charge heterogeneity of mAbs. However, as the method relies on a non-volatile background electrolyte (BGE), it cannot be directly hyphenated with mass spectrometry (MS), hampering the identification of separated charge variants., Results: This study presents a CZE-UV/MS method using a neutral static capillary coating of hydroxypropyl methylcellulose combined with a volatile BGE at pH 5.0 to allow for MS-compatible mAb charge variant separations. The effect of several parameters, including pH and concentration of the BGE, applied voltage, and injected mAb concentrations on separation performance was investigated using a panel of commercially available mAbs. The optimized method was evaluated with IgG 1 and IgG 4 mAbs of varying pI (7.4-9.2) and degrees of heterogeneity. Basic and acidic variants were separated from the parent mAb using a BGE of 50 mM acetic acid adjusted to pH 5.0 with ammonium hydroxide. The relative abundances of charge variants determined with the new method showed a good correlation with the corresponding relative levels obtained with the method of He et al. CZE-MS coupling was accomplished using the nanoCEasy, a low-flow sheath liquid interface, which enabled the identification and quantitation of basic, acidic, and incomplete pyroglutamate variants, and glycoforms of the tested mAbs., Significance: This manuscript describes a new CZE-MS method that permits heterogeneity assessment of mAbs under MS-compatible conditions, providing charge variant separation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Polyesters are applied in high-end products in many industrial applications, including resins and powder-coating applications. The characterization of the chemical heterogeneities within a polyester is of utmost interest to develop new products or improve existing applications. Unfortunately, characterization is a difficult task, as polyesters may feature distributions in end-group functionality, molecular weight, chemical composition, and degree of branching. Currently, no analytical method can characterize all these interdependent distributions in a single analysis., Results: We report the use of comprehensive normal-phase liquid chromatography × size-exclusion chromatography hyphenated with ultraviolet-light spectroscopy and high-resolution mass spectrometry in parallel (NPLC × SEC-UV/HRMS) to characterize polyesters according to their end-group-functionality and molecular-weight distributions. The chemical composition can be measured with HRMS, while relative quantitation can be performed with UV detection. A supercharging agent was used during ionization allowing to extend the molecular-weight range of the detected chemical species., Significance: The presented platform allows characterization of polyesters with varying fractions of carboxyl or hydroxyl end-group functionalities and varying distributions of molecular weight, degree of branching, and chemical compositions. The number-average and weight-average molar masses are obtained in the same analysis. This information cannot be obtained by any one-dimensional technique. The developed NPLC × SEC-UV/HRMS platform is a valuable tool for characterizing polyesters in an industrial setting., Competing Interests: Declaration of competing interest “The authors declare that they have no known competing financial interest or personal relationship that could have appeared to influence the work reported in this paper.”, (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Comprehensive two-dimensional chromatography generates complex data sets, and numerous baseline correction and noise removal algorithms have been proposed in the past decade to address this challenge. However, evaluating their performance objectively is currently not possible due to a lack of objective data., Result: To tackle this issue, we introduce a versatile platform that models and reconstructs single-trace two-dimensional chromatography data, preserving peak parameters. This approach balances real experimental data with synthetic data for precise comparisons. We achieve this by employing a Skewed Lorentz-Normal model to represent each peak and creating probability distributions for relevant parameter sampling. The model's performance has been showcased through its application to two-dimensional gas chromatography data where it has created a data set with 458 peaks with an RMSE of 0.0048 or lower and minimal residuals compared to the original data. Additionally, the same process has been shown in liquid chromatography data., Significance: Data analysis is an integral component of any analytical method. The development of new data processing strategies is of paramount importance to tackle the complex signals generated by state-of-the-art separation technology. Through the use of probability distributions, quantitative assessment of algorithm performance of new algorithms is now possible. Therefore, creating new opportunities for faster, more accurate, and simpler data analysis development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

The time required for method development in gradient-elution liquid chromatography (LC) may be reduced by using an empirical modelling approach to describe and predict analyte retention and peak width. However, prediction accuracy is impaired by system-induced gradient deformation, which can be especially prominent for steep gradients. As the deformation is unique to each LC instrument, it needs to be corrected for if retention modelling for optimization and method transfer is to become generally applicable. Such a correction requires knowledge of the actual gradient profile. The latter has been measured using capacitively coupled "contactless" conductivity detection (C 4 D), featuring a low detection volume (approximately 0.05 μL) and compatibility with very high pressures (80 MPa or more). Several different solvent gradients, from water to acetonitrile, water to methanol, and acetonitrile to tetrahydrofuran, could be measured directly without the addition of a tracer component to the mobile phase, exemplifying the universal nature of the approach. Gradient profiles were found to be unique for each solvent combination, flowrate, and gradient duration. The profiles could be described by convoluting the programmed gradient with a weighted sum of two distribution functions. Knowledge of the exact profiles was used to improve the inter-system transferability of retention models for toluene, anthracene, phenol, emodin, sudan-I and several polystyrene standards., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

New psychoactive substances (NPS) are synthetic derivatives of illicit drugs designed to mimic their psychoactive effects. NPS are typically not controlled under drug acts or their legal status depends on their molecular structure. Discriminating isomeric forms of NPS is therefore crucial for forensic laboratories. In this study, a trapped ion mobility spectrometry time-of-flight mass spectrometry (TIMS-TOFMS) approach was developed for the identification of ring-positional isomers of synthetic cathinones, a class of compounds representing two-third of all NPS seized in Europe in 2020. The optimized workflow features narrow ion-trapping regions, mobility calibration by internal reference, and a dedicated data-analysis tool, allowing for accurate relative ion-mobility assessment and high-confidence isomer identification. Ortho-, meta- and para-isomers of methylmethcathinone (MMC) and bicyclic ring isomers of methylone were assigned based on their specific ion mobilities within 5 min, including sample preparation and data analysis. The resolution of two distinct protomers per cathinone isomer added to the confidence in identification. The developed approach was successfully applied to the unambiguous assignment of MMC isomers in confiscated street samples. These findings demonstrate the potential of TIMS-TOFMS for forensic case work requiring fast and highly-confident assignment cathinone-drug isomers in confiscated samples., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)